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Meta·Software Engineer·Onsite - Product Sense / Strategy·Senior

Senior
May 2026

Summary

Product design question for an EM role at Meta. Just the one question but it had enough surface area to go in a lot of directions, which made it weirdly harder than expected.

Questions Asked (1)

Q1

How would you design a 'Hot Topics' feature for Instagram?

Product Sense & IdeationProduct StrategyProduct Analytics & Metrics
Author's notes

I went straight to the feed ranking angle and spent too long there before realizing they probably wanted me to think about the full feature, discovery surfaces, content aggregation, moderation considerations.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the goal of 'Hot Topics'—likely to surface trending content and increase engagement—and define success metrics. Then outline a high-level design covering data sources, ranking algorithms, and user interface, while addressing scalability and privacy. Finally, discuss trade-offs and potential iterations.

Pro tip: Emphasize how you would leverage existing Instagram infrastructure (e.g., hashtags, Explore) to bootstrap the feature, and propose A/B tests to validate engagement lift before full rollout.

1. Clarify Requirements and Goals

Ask questions to understand the feature's purpose, target users, and success metrics (e.g., increase time spent, DAU). Define what 'hot' means (e.g., rapidly growing engagement).

2. High-Level Design

Outline the system components: data ingestion (posts, hashtags, interactions), processing (trend detection, ranking), storage, and serving. Consider real-time vs batch processing.

3. Ranking and Personalization

Describe how to rank topics: use signals like velocity, volume, diversity, and user affinity. Discuss personalization to avoid echo chambers and ensure freshness.

4. User Interface and Integration

Propose where the feature appears (e.g., Explore tab, search, notifications) and how users interact. Ensure seamless integration with existing Instagram UI.

5. Metrics, Testing, and Iteration

Define success metrics (CTR, engagement, retention) and outline A/B testing plan. Discuss potential risks (e.g., spam, misinformation) and mitigation.

Key Points to Mention

  • Use existing signals like hashtags, likes, comments, and shares to detect trends.
  • Implement a scalable architecture (e.g., stream processing with Kafka, Flink) to handle real-time data.
  • Incorporate personalization to show relevant hot topics to each user.
  • Address privacy and safety: filter out sensitive or harmful content.
  • Define clear success metrics and run A/B tests to measure impact.
  • Consider cold-start problem and how to bootstrap the feature.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.